/// <summary>
/// Performs DiviK clustering on the specified data.
/// </summary>
/// <param name="dataset">Input dataset.</param>
/// <param name="options">Configuration.</param>
/// <returns>Segmentation result.</returns>
/// <exception cref="System.ObjectDisposedException">thrown if this object has been disposed.</exception>
public DivikResult Divik(IDataset dataset, DivikOptions options)
{
// This is needed to not to make MCR go wild
const int numberOfOutputArgs = 2;
var coordinates = dataset.GetRawSpacialCoordinates(is2D: true);
var coords = new double[coordinates.GetLength(dimension: 0), coordinates.GetLength(dimension: 1)];
for (var i = 0; i < coordinates.GetLength(dimension: 0); ++i)
{
for (var j = 0; j < coordinates.GetLength(dimension: 1); ++j)
{
coords[i, j] = coordinates[i, j];
}
}
var varargin = options.ToVarargin();
var matlabDivikResult = _segmentation.divik(
numberOfOutputArgs,
dataset.GetRawIntensities(),
coordinates,
varargin);
// matlabResult[0] is equal to the "partition" field in matlabResult[1], that's why we only use matlabResult[1]
// Besides it helps to create recursive single constructor for DivikResult
var result = new DivikResult(matlabResult: matlabDivikResult[Segmentation.DivikStructureLocation]);
return(result);
}
/// <summary>
/// Estimates the GMM model from the data set.
/// </summary>
/// <param name="dataset">Input dataset.</param>
/// <returns>Estimated model</returns>
/// <exception cref="System.ObjectDisposedException">thrown if this object has been disposed.</exception>
public GmmModel EstimateGmm(IDataset dataset)
{
ValidateDispose();
var originalMz = dataset.GetRawMzArray();
var matlabModel = _gmm.estimate_gmm(originalMz, data: dataset.GetRawIntensities());
var model = new GmmModel(matlabModel, originalMz);
return(model);
}
/// <summary>
/// Normalizes dataset by TIC-based method.
/// </summary>
/// <param name="dataset">Input dataset.</param>
/// <returns>Normalized dataset.</returns>
/// <exception cref="System.ObjectDisposedException">thrown if this object has been disposed.</exception>
public IDataset NormalizeByTic(IDataset dataset)
{
ValidateDispose();
var normalizationResult = _preprocessing.ticnorm(data: dataset.GetRawIntensities());
return(new BasicTextDataset(
mz: dataset.GetRawMzArray(),
data: (double[, ])normalizationResult,
coordinates: dataset.GetRawSpacialCoordinates(is2D: true)));
}
public void GetRawIntensitiesTest()
{
var result = _dataset.GetRawIntensities();
Assert.AreEqual(result,
actual: new[, ] {
{ 1, 2.1, 3.2 }, { 4, 5.1, 6.2 }, { 7, 8.1, 9.2 }
},
message: "Dataset returned wrong intensity row.");
}
/// <summary>
/// Removes the baseline.
/// </summary>
/// <param name="dataset">Input dataset.</param>
/// <returns>Dataset without baseline.</returns>
/// <exception cref="System.ObjectDisposedException">thrown if this object has been disposed.</exception>
public IDataset RemoveBaseline(IDataset dataset)
{
ValidateDispose();
var baselineRemovalResult =
_preprocessing.remove_baseline(mz: dataset.GetRawMzArray(), data: dataset.GetRawIntensities());
return(new BasicTextDataset(
mz: dataset.GetRawMzArray(),
data: (double[, ])baselineRemovalResult,
coordinates: dataset.GetRawSpacialCoordinates(is2D: true)));
}
/// <summary>
/// Applies the GMM model onto data.
/// </summary>
/// <param name="model">The model.</param>
/// <param name="dataset">Input dataset.</param>
/// <returns>Convolved data.</returns>
/// <exception cref="System.ObjectDisposedException">thrown if this object has been disposed.</exception>
/// <exception cref="InvalidOperationException">Applying model build on different m/z axis.</exception>
public IDataset ApplyGmm(GmmModel model, IDataset dataset)
{
ValidateDispose();
if (!dataset.GetRawMzArray()
.SequenceEqual(model.OriginalMz))
{
throw new InvalidOperationException(message: "Applying model built on different m/z axis.");
}
var matlabModel = model.MatlabStruct;
var applyResult = _gmm.apply_gmm(matlabModel, data: dataset.GetRawIntensities(), mz: dataset.GetRawMzArray());
var data = (double[, ])((MWStructArray)model.MatlabStruct).GetField(fieldName: "mu");
var mz = new double[data.GetLength(dimension: 0)];
Buffer.BlockCopy(data, srcOffset: 0, dst: mz, dstOffset: 0, count: data.GetLength(dimension: 0));
return(new BasicTextDataset(mz, data: (double[, ])applyResult, coordinates: dataset.GetRawSpacialCoordinates(is2D: true)));
}
/// <summary>
/// Perform FFT-based peak alignment.
/// </summary>
/// <param name="dataset">Input dataset.</param>
/// <returns>Aligned dataset.</returns>
/// <exception cref="System.ObjectDisposedException">thrown if this object has been disposed.</exception>
public IDataset AlignPeaksFft(IDataset dataset)
{
ValidateDispose();
var pafftResult = _preprocessing.pafft(mz: dataset.GetRawMzArray(), data: dataset.GetRawIntensities());
return(new BasicTextDataset(
mz: dataset.GetRawMzArray(),
data: (double[, ])pafftResult,
coordinates: dataset.GetRawSpacialCoordinates(is2D: true)));
}
